Transitioning from a computerized provider order entry and paper documentation system to an electronic health record: expectations and experiences of hospital staff.

OBJECTIVES: To examine healthcare worker's perceptions, expectations, and experiences regarding how work processes, patient-related safety, and care were affected when a quaternary care center transitioned from one computerized provider order entry (CPOE) system to a full electronic health record (EHR). METHODS: The I-SEE survey was administered prior to and 1-year after transition in systems. The construct validity and reliability of the survey was assessed within the current population and also compared to previously published results. Pre- and 1-year post-implementation scale means were compared within and across time periods. RESULTS: The majority of respondents were nurses and personnel working in the acute care setting. Because a confirmatory factor analysis indicated a lack of fit of our data to the I-SEE survey's 5-factor structure, we conducted an exploratory factor analysis that resulted in a 7-factor structure which showed better reliability and validity. Mean scores for each factor indicated that attitudes and expectations were mostly positive and score trends over time were positive or neutral. Nurses generally had less positive attitudes about the transition than non-nursing respondents, although the difference diminished after implementation. CONCLUSIONS: Findings demonstrate that the majority of responding staff were generally positive about transitioning from CPOE system to a full electronic health record (EHR) and understood the goals of doing so, with overall improved ratings over time. In addition, the I-SEE survey, when modified based on our population, was useful for assessing patient care and safety related expectations and experiences during the transition from one CPOE system to an EHR.

Assessing the reliability of an automated dose-rounding algorithm.

OBJECTIVE: Pediatric dose rounding is a unique and complex process whose complexity is rarely supported by e-prescribing systems, though amenable to automation and deployment from a central service provider. The goal of this project was to validate an automated dose-rounding algorithm for pediatric dose rounding. METHODS: We developed a dose-rounding algorithm, STEPSTools, based on expert consensus about the rounding process and knowledge about the therapeutic/toxic window for each medication. We then used a 60% subsample of electronically-generated prescriptions from one academic medical center to further refine the web services. Once all issues were resolved, we used the remaining 40% of the prescriptions as a test sample and assessed the degree of concordance between automatically calculated optimal doses and the doses in the test sample. Cases with discrepant doses were compiled in a survey and assessed by pediatricians from two academic centers. The response rate for the survey was 25%. RESULTS: Seventy-nine test cases were tested for concordance. For 20 cases, STEPSTools was unable to provide a recommended dose. The dose recommendation provided by STEPSTools was identical to that of the test prescription for 31 cases. For 14 out of the 24 discrepant cases included in the survey, respondents significantly preferred STEPSTools recommendations (p<0.05, binomial test). Overall, when combined with the data from all test cases, STEPSTools either matched or exceeded the performance of the test cases in 45/59 (76%) of the cases. The majority of other cases were challenged by the need to provide an extremely small dose. We estimated that with the addition of two dose-selection rules, STEPSTools would achieve an overall performance of 82% or higher. CONCLUSIONS: Results of this pilot study suggest that automated dose rounding is a feasible mechanism for providing guidance to e-prescribing systems. These results also demonstrate the need for validating decision-support systems to support targeted and iterative improvement in performance.